THEMATIC PROGRAMS

July 24, 2014

Thematic Program on Causal Interpretation and Identification of Conditional Independence Structures

September to November 1999

Organizing Committee:
Hélène Massam (University of Virginia), David Tritchler (University of Toronto)

Scientific Committee:
Phil Dawid (University College, London),
Steffen Lauritzen (Aalborg University),
Michael Perlman (University of Washington)

The aim of this research program is threefold:

  • To bring together a group of eminent researchers in subdisciplines of Statistics, Probability, Algebra, Artificial Intelligence, and some areas of applications to improve on the current understanding of the basic structures of Highly Structured Stochastic Systems (HSSS) models.
  • To train graduate students in statistics, and researchers in areas of applications, in newly developed techniques. It is particularly important that graduate students be exposed to a variety of disciplines involved in the study of HSSS so that they may take a multidisciplinary approach in their research. In such workshops, students should also update their computational skills to be able to use and understand some of the most recent computational methods.
  • To offer short courses, applicable to business, medical or social sciences, to introduce already developed software to non-specialists who are in decision-making positions (i.e. epidemiologists, consultants in investments, sociologists, etc.)

SHORT COURSES

The following courses are aimed at graduate students, session participants and non-specialists in statistics:

SEPTEMBER 20 - OCTOBER 22, 1999
Course 1: Graphical Markov Models
Steen Andersson (Indiana University)

SEPTEMBER 20 - OCTOBER 1, 1999
Course 2: Linear Structural Equations and Graphical Models
Jan Koster (Erasmus University)

OCTOBER 27 - OCTOBER 29, 1999
Short Course 1: Diagnosing and Planning with Bayesian Networks and Influence Diagrams (A Practical Guide)
Uffe Kjærulff (Aalborg University) and Kristian Olesen (Aalborg University)

NOVEMBER 15 - NOVEMBER 16, 1999
Short Course 2: Graphical Markov Models: Their Role in Statistical Analysis of Data Generating Processes
David Cox (Nuffield College, Oxford) and Nanny Wermuth (ZUMA - Center for Survey Research, Mannheim)

LECTURES -- SEWALL WRIGHT LECTURE SERIES

Judea Pearl (University of California)
"The Mathematics of Cause and Effect"
October 25, 3:30 p.m. to 5:30 p.m.
October 26, 3:00 p.m. to 5:00 p.m.

Glenn Shafer (Rutgers University)
"The Language of Causality"
November 4, 3:30 p.m. to 5:30 p.m.
November 9, 3:30 p.m. to 5:30 p.m.

SEMINARS

For experts in the different fields represented, we plan longer research seminars discussing the latest developments:

SEPTEMBER 27 - OCTOBER 8, 1999
Seminar 1: Causal Interpretation of Graphical Models
Phil Dawid (University College, London) and Glenn Shafer (Rutgers University)

OCTOBER 11 - 29, 1999
Seminar 2: Relating Causal Structure to Conditional Independence Structure
Thomas Richardson (University of Warwick) and Peter Spirtes (Carnegie Mellon University)

NOVEMBER 2 - 12, 1999
Seminar 3: Learning Causal Models
David Heckerman (Microsoft Research) and Steffen Lauritzen (Aalborg University)

SEPTEMBER 27 - OCTOBER 15, 1999
Seminar 4: Conditional Independence Structures
Milan Studený and Frantisek Matús (Academy of Science of Czech Republic)

OCTOBER 25 - NOVEMBER 12, 1999
Seminar 5: Algebraic Methods in Graphical Markov Models
Steen Andersson (Indiana University), Gérard Letac (Université Paul Sabatier), Michael Perlman, (University of Washington) and Hélène Massam (University of Virginia)